Top Artificial Intelligence Jobs in Des Moines, IA

Owns the end-to-end deployment of unmanned forklifts, from project kickoff and planning through on-site setup, commissioning, validation, and completion reporting. Acts as the technical liaison among customers, engineering teams, SI partners, manufacturers, and ODM vendors. Responsibilities include requirements analysis, project scheduling, system integration support, troubleshooting, stakeholder communication, deployment documentation, and field feedback. Requires extended travel and assignments in warehouses or industrial environments.

Owns the mortgage platform’s product strategy, roadmap, feature prioritization, and execution. Analyzes market, customer, and competitive needs; acts as product evangelist and subject-matter expert; and collaborates with development and business analysis teams to deliver software products. The role requires mortgage loan origination expertise, experience building integration-heavy software products, familiarity with AI tools, technical and strategic judgment, agile development knowledge, and strong communication and leadership skills.

Own full-cycle recruiting for technical and go-to-market roles during a six-month contract. Source and assess candidates, coordinate interviews, maintain recruiting pipelines in Ashby, advise hiring managers using market and candidate insights, support offers and negotiations, and improve recruiting processes. The role requires independent execution, strong sourcing skills, familiarity with the San Francisco Bay Area talent market, and the ability to manage multiple searches in a fast-paced environment.

Design, develop, and maintain scalable backend systems for a composite AI platform (agent-based systems, LLM integrations, RAG). Own technical vision and roadmap, make architecture decisions, establish engineering best practices, provide senior technical leadership, and deliver high-impact production software.

Build and operate security-critical backend systems in Python, including encryption, key management, sensitive-data controls, credential protection, tenant isolation, authentication, signing, and token handling. Own projects end to end from investigation and architecture through implementation, migration, staged rollout, observability, and recovery. The role requires applied cryptography, strong trust-boundary judgment, and experience safely evolving systems handling sensitive or regulated data across cloud, VPC, and on-premises deployments.

Own enterprise customer accounts from onboarding through renewal and expansion. Monitor customer health, usage, and outcomes; conduct QBRs; drive adoption and growth; support integrations, workflow design, launches, and training; maintain CRM and billing records; resolve issues cross-functionally; advocate for customers; and build relationships with technical and executive stakeholders.

Lead client-facing AI adoption and transformation engagements for mid-market companies. Design and facilitate practical sessions for executives and teams, demonstrate AI use cases, adapt to participant needs, manage client relationships between sessions, support adoption, advise on AI strategy and policy, evaluate evolving tools, and report field insights. Success is measured through behavior change, sustained AI usage, and business results.

Build full-stack AI-powered video creation and collaboration tools, including rich multimedia interfaces, backend APIs, server-side processes, LLM-powered features, and conversational experiences. Work with generative AI, computer vision, and machine learning models in production. Improve system performance, reliability, and code quality while rapidly prototyping and delivering product features in a collaborative, high-ownership environment.

Lead and coach a team of Technical Customer Support Specialists; own escalation playbooks, KPIs, and L2 technical investigations. Partner with Product and Engineering to resolve systemic issues, hire and onboard new reps, and ensure empathetic clinician-centered support.

Build and operate large-scale data pipelines, web-scraping systems, and data-collection tools for AI datasets. Maintain analytical databases, optimize queries, troubleshoot pipeline and data-quality issues, manage containerized workloads across Kubernetes and Linux infrastructure, and support CI/CD workflows. The role also involves documenting technical processes, researching improvements, and developing scalable APIs in a fully remote environment.